Tamburini_AVIDseq

Cell type markers

# Cell type colors
cell_types <- unique(sobj$cell_typeDC)
names(cell_types) <- cell_types

type_cols <- theme_cols
names(type_cols) <- cell_types
type_cols <- type_cols[!is.na(names(type_cols))]

# Find all cell type markers
Idents(sobj) <- sobj %>%
  FetchData("cell_typeDC")

all_type_marks <- sobj %>%
  FindAllMarkers(only.pos = T) %>%
  as_tibble() %>%
  filter(p_val_adj < 0.05)

# Cell type UMAP
type_umap <- sobj %>%
  plot_features(
    feature     = "cell_typeDC",
    plot_cols   = type_cols,
    feat_levels = names(type_cols)
  ) +
  guides(color = col_guide) +
  blank_theme +
  theme(
    legend.position = "top",
    legend.title    = element_blank(),
    legend.text     = element_text(size = 10)
  )

# Marker plots
for (i in seq_along(type_cols)) {
  cat("\n### **", names(type_cols[i]), "**\n", sep = "")
  
  type_marks <- all_type_marks %>%
    filter(cluster == names(type_cols[i]))
  
  type_marks_fig <- sobj %>%
    create_marker_fig(
      input_markers = type_marks,
      type_id       = "cell_typeDC",
      input_umap    = type_umap,
      umap_color    = type_cols[[i]],
      box_colors    = type_cols
    )
  
  # type_marks %>%
  #   kable() %>%
  #   kable_styling(fixed_thead = T) %>%
  #   print()

  print(type_marks_fig)
  cat("\n\n---\n\n<br>\n\n<br>\n\n")
}

cDC2 Tbet-

CCR7hi mig cDC2

Monocyte

CCR7hi Langerhans

cDC1

CCR7hi mig cDC1

CCR7hi XCR1- mig cDC2

Cell cluster markers

# Cell type colors
cell_clusts <- sobj@meta.data %>%
  mutate(
    type_clust = str_extract(cell_typeDC2, "^[0-9]+"),
    type_clust = as.numeric(type_clust)
  ) %>%
  arrange(cell_typeDC, type_clust) %>%
  pull(cell_typeDC2) %>%
  unique()

names(cell_clusts) <- cell_clusts

clust_cols <- theme_cols
names(clust_cols) <- cell_clusts
clust_cols <- clust_cols[!is.na(names(clust_cols))]

# Find all cell cluster markers
Idents(sobj) <- sobj %>%
  FetchData("cell_typeDC2")

all_clust_marks <- sobj %>%
  FindAllMarkers(only.pos = T) %>%
  as_tibble() %>%
  filter(p_val_adj < 0.05)

# Cluster UMAP
clust_umap <- sobj %>%
  plot_features(
    feature     = "cell_typeDC2",
    plot_cols   = clust_cols,
    feat_levels = names(clust_cols)
  ) +
  guides(color = col_guide) +
  blank_theme +
  theme(
    legend.position = "top",
    legend.title    = element_blank(),
    legend.text     = element_text(size = 10)
  )

# Cluster plots
for (i in seq_along(clust_cols)) {
  cat("\n### **", names(clust_cols[i]), "**\n", sep = "")
  
  clust_marks <- all_clust_marks %>%
    filter(cluster == names(clust_cols[i]))
  
  clust_marks_fig <- sobj %>%
    create_marker_fig(
      input_markers = clust_marks,
      type_id       = "cell_typeDC2",
      input_umap    = clust_umap,
      umap_color    = clust_cols[[i]],
      box_colors    = clust_cols
    )
  
  print(clust_marks_fig)
  cat("\n\n---\n\n<br>\n\n<br>\n\n")
}

11-CCR7hi Langerhans

3-CCR7hi mig cDC1

0-CCR7hi mig cDC2

6-CCR7hi mig cDC2

7-CCR7hi mig cDC2

12-CCR7hi mig cDC2

5-CCR7hi XCR1- mig cDC2

9-cDC1

14-cDC1

16-cDC1

1-cDC2 Tbet-

2-cDC2 Tbet-

4-cDC2 Tbet-

8-cDC2 Tbet-

10-cDC2 Tbet-

13-cDC2 Tbet-

15-cDC2 Tbet-

17-Monocyte

Separate cell cluster markers

# Find cluster markers separately for each cell type
sep_clust_marks <- cell_types %>%
  map(find_sep_clust_markers, sobj) %>%
  compact() %>%
  bind_rows()

sep_clusts <- sep_clust_marks$cluster %>%
  unique()

sep_clusts <- clust_cols[names(clust_cols) %in% sep_clusts] %>%
  names()

# Cluster plots
for (i in seq_along(sep_clusts)) {
  cat("\n### **", sep_clusts[i], "**\n", sep = "")
  
  sep_marks <- sep_clust_marks %>%
    filter(cluster == sep_clusts[i])
  
  type <- sep_clusts[i] %>%
    str_remove("^[0-9]+-")
  
  sep_cols <- clust_cols[grepl(str_c("-", type), names(clust_cols))]
  sep_cols <- c(sep_cols, "Other" = "#f0f0f0")
  
  sep_clust_umap <- sobj %>%
    FetchData(c("UMAP_1", "UMAP_2", "cell_typeDC", "cell_typeDC2")) %>%
    as_tibble(rownames = "cell_id") %>%
    mutate(cell_typeDC2 = if_else(cell_typeDC != type, "Other", cell_typeDC2)) %>%
    plot_features(
      feature     = "cell_typeDC2",
      plot_cols   = sep_cols,
      feat_levels = names(sep_cols)
    ) +
    guides(color = col_guide) +
    blank_theme +
    theme(
      legend.position = "top",
      legend.title    = element_blank(),
      legend.text     = element_text(size = 10)
    )
  
  sep_clust_marks_fig <- sobj %>%
    create_marker_fig(
      input_markers  = sep_marks,
      type_id        = "cell_typeDC2",
      input_umap     = sep_clust_umap,
      umap_color     = sep_cols[sep_clusts[i]],
      box_colors     = sep_cols,
      cell_type      = type
    )
  
  print(sep_clust_marks_fig)
  cat("\n\n---\n\n<br>\n\n<br>\n\n")
}